Bharat Bhavnasi

I Tested Every Major Open-Source AI Agent SDK So You Don't Have To

• 2 min read
#ai #agents #open-source #sdk #development
I Tested Every Major Open-Source AI Agent SDK So You Don't Have To

I spent weeks testing every major open-source AI agent SDK so you don’t have to. Here’s what actually matters when choosing your framework.

The Frameworks

I evaluated seven frameworks across multiple dimensions including real-world usability, extensibility, and developer experience:

  1. CrewAI (Python) — Multi-agent orchestration
  2. LangChain (TypeScript) — Functional composition
  3. LangGraph.js (TypeScript) — State machine workflows
  4. DeepAgents.js (TypeScript) — Strategic planning with memory
  5. Mastra (TypeScript) — Full-stack framework with dependency injection
  6. Google ADK-JS (TypeScript) — Multi-platform modular design
  7. AWS AgentCore (TypeScript) — Cloud-native runtime with sandboxing

What Actually Matters

Rather than declaring one “best” framework, here’s the truth: there’s no single winner—but there are clear winners depending on what you’re actually trying to build.

Different tools excel in different areas:

  • Multi-agent coordination — How well can multiple agents work together?
  • State management — How are conversations and context maintained?
  • Deployment options — What are your hosting and scaling requirements?
  • Architectural philosophy — Does the framework match your mental model?
  • Community support — How active is development and community engagement?

Evaluation Criteria

My analysis considered:

  • Feature completeness and maturity
  • Architecture patterns and design philosophy
  • Memory handling and context management
  • Community support and ecosystem
  • Practical implementation challenges
  • Real-world deployment considerations

Key Insights

The ranking depends on your specific use case requirements. What works great for a small prototype might not scale for production. What’s elegant for a Python multi-agent system might be overkill for a simple conversational assistant.

Rather than relying solely on marketing materials, this analysis draws from hands-on testing and practical insights from developers actively deploying these frameworks.

Get the Full Analysis

Check out the detailed GitHub repository containing the complete analysis, built with Claude Opus 4.5:

📍 GitHub Repository: https://github.com/bvsbharat/open-agent-sdks

The repo includes side-by-side comparisons, code examples for each framework, and practical recommendations for different use cases.

The Bottom Line

Choose your AI agent SDK based on:

  1. Your specific use case and requirements
  2. Your team’s language and framework expertise
  3. Your deployment and scaling needs
  4. The maturity and community support you need

There’s no universal “best”—only what’s best for your project.

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